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Recap from It's a Free Country.

Welcome to Politics Bites, where every afternoon at It's A Free Country, we bring you the unmissable quotes from the morning's political conversations on WNYC. Today on the Brian Lehrer Show, Sasha Issenberg of Slate talks about the different ways campaigns—including the Obama administration—are using data analytics to target their message to voters.  He wrote the piece titled, "Dreamcatcher."

Project Dreamcatcher

Campaigns are watching you.

In a recent article for Slate, Sasha Issenberg detailed new technology that presidential campaigns are using to mine and organize data about voters. Campaigns can then use this information—collected in person; through public records; or, increasingly, online—to produce personalized ads and communications, ones that use your name, or addresses issues important to you—and in terms that resonate with you.

Digital text analytics, Issenberg said, has made the business of "microtargeting" voters all the more savvy.

It's all well and good to throw web ads at people and get them to move in and out of a site, but if you don't know who they are or where they vote or what party they are, it's either inefficient or often counterproductive.

Issenberg writes in his article that the Obama campaign's "Project Dreamcatcher" is one such analytic initiative meant to solve these problems: "If a voter writes in a Web form that her top concern is the war in Afghanistan, should she be asked [by the Obama campaign] to enlist as a 'Veterans for Obama' volunteer, or sent direct mail written to placate foreign-policy critics?"

Revenge of the nerds

Until recently, there was no way for campaigns to answer that question. It used to be that a staffer could go door-to-door asking something like "Romney or Obama?" and collect responses that translate nicely into usable data: the answer to that kind of question can be a 1 or a 2, Issenberg explained.

But the reasons why Romney or Obama, or whoever else, wasn't easily converted into data. Now that technology allows campaigns the space to store ever-increasing quantities of information, the means to measure that information analytically, and the opporunity to build complex mathematical functions that can predict effective outreach strategies—getting pretty geeky, right?—the game has changed.

That information often had nowhere to go, and so it doesn't easily turn into a 1 or a 2. The challenge of the Dreamcatcher project is to effectively turn that into a number that can then be pooled with all the other stuff that is easily represented as numbers. Once you have all these as variables that can be interchanged, you can build algorithms that can be predictive.

What campaigns learned from catalogs

Issenberg pointed out that voters may not recognize just how much campaigning has evolved. The house looks the same, he said, but the plumbing's gotten extremely complicated.

To voters, campaigns are going to look a lot like they did in 2008. But there are these major innovations going on behind the scenes at campaigns based on how they use data, and it's going to be very hard for voters to understand whats going on.

Perhaps there's a simpler way to put it.

The information that campaigns in the 1980s used to decide whether to send you a flyer has now been merged with the information that L.L. Bean used in the 1990s to send you a catalog.